Filter.py 文件源码

def fft_convolve_1d(x: np.ndarray, h: np.ndarray):
        n = len(x) + len(h) - 1
        n_opt = 1 << (n - 1).bit_length()  # Get next power of 2
        if np.issubdtype(x.dtype, np.complexfloating) or np.issubdtype(h.dtype, np.complexfloating):
            fft, ifft = np.fft.fft, np.fft.ifft  # use complex fft
        else:
            fft, ifft = np.fft.rfft, np.fft.irfft  # use real fft

        result = ifft(fft(x, n_opt) * fft(h, n_opt), n_opt)[0:n]
        too_much = (len(result) - len(x)) // 2  # Center result
        return result[too_much: -too_much]